{"id":"https://openalex.org/W3010221856","doi":"https://doi.org/10.1109/gcce46687.2019.9015318","title":"Full Reference Image Quality Assessment by CNN Feature Maps and Visual Saliency","display_name":"Full Reference Image Quality Assessment by CNN Feature Maps and Visual Saliency","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W3010221856","doi":"https://doi.org/10.1109/gcce46687.2019.9015318","mag":"3010221856"},"language":"en","primary_location":{"id":"doi:10.1109/gcce46687.2019.9015318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce46687.2019.9015318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060201461","display_name":"Yu Iwashima","orcid":null},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yu Iwashima","raw_affiliation_strings":["Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101464181","display_name":"Ji Wang","orcid":"https://orcid.org/0000-0001-7077-3402"},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Ji Wang","raw_affiliation_strings":["Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5110603628","display_name":"Yoshiyuki Yashima","orcid":null},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshiyuki Yashima","raw_affiliation_strings":["Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan"],"affiliations":[{"raw_affiliation_string":"Graduate School of Information Science, Chiba Institute of Technology, Narashino, Japan","institution_ids":["https://openalex.org/I8488066"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060201461"],"corresponding_institution_ids":["https://openalex.org/I8488066"],"apc_list":null,"apc_paid":null,"fwci":0.4049,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.67128824,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"203","last_page":"207"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.822292685508728},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7887887954711914},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7422071695327759},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6995591521263123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6668566465377808},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5323102474212646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5043691396713257},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.4847809672355652},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4628424346446991},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.45627349615097046},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.43085697293281555},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4195594787597656},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.41185569763183594}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.822292685508728},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7887887954711914},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7422071695327759},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6995591521263123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6668566465377808},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5323102474212646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5043691396713257},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.4847809672355652},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4628424346446991},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.45627349615097046},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.43085697293281555},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4195594787597656},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.41185569763183594},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce46687.2019.9015318","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce46687.2019.9015318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W44558019","https://openalex.org/W874645128","https://openalex.org/W1964859077","https://openalex.org/W2114582993","https://openalex.org/W2128272608","https://openalex.org/W2133665775","https://openalex.org/W2141983208","https://openalex.org/W2142884912","https://openalex.org/W2146103513","https://openalex.org/W2509123681","https://openalex.org/W2576670953","https://openalex.org/W2793583884"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4313906399","https://openalex.org/W4321487865","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W2318112981","https://openalex.org/W4312417841","https://openalex.org/W4225147082","https://openalex.org/W2778653980"],"abstract_inverted_index":{"In":[0,49],"this":[1],"paper,":[2],"we":[3,51],"propose":[4],"a":[5,34],"new":[6],"full":[7],"reference":[8],"image":[9,62,90],"quality":[10,63,91],"estimation":[11,92],"method":[12,30,102],"by":[13,103],"feature":[14,43,57],"maps":[15,44,58],"which":[16,55,76],"are":[17,59,70,77],"intermediate":[18],"layer's":[19,56],"outputs":[20],"in":[21,53],"convolutional":[22,46],"neural":[23,47,79],"network.":[24,48],"The":[25],"novelty":[26],"of":[27,45],"the":[28,42,85,89,100,105],"proposed":[29],"is":[31],"to":[32,99],"combine":[33],"saliency":[35,106],"map":[36],"reflecting":[37],"human":[38],"gaze":[39],"area":[40],"with":[41],"addition,":[50],"analyze":[52],"detail":[54],"effective":[60],"for":[61,81],"estimation.":[64],"Experiments":[65],"using":[66],"CID:IQ":[67],"data":[68],"set":[69],"performed":[71],"on":[72],"VGG16":[73],"and":[74,84],"VGG19":[75],"deep":[78],"networks":[80],"object":[82],"recognition,":[83],"results":[86],"show":[87],"that":[88],"accuracy":[93],"can":[94],"be":[95],"significantly":[96],"improved":[97],"compared":[98],"conventional":[101],"introducing":[104],"map.":[107]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
